Search

The complex pathogenesis of rheumatoid arthritis (RA) is not fully understood, with few studies exploring the genomic contribution to RA in patients from Africa. We report a genome-wide association study (GWAS) of South-Eastern Bantu-Speaking South Africans (SEBSSAs) with seropositive RA (n = 531) and population controls (n = 2653). Association testing was performed using PLINK (logistic regression assuming an additive model) with sex, age, smoking and the first three principal components as covariates. The strong association with the Human Leukocyte Antigen (HLA) region, indexed by rs602457 (near HLA-DRB1), was replicated. An additional independent signal in the HLA region represented by the lead SNP rs2523593 (near the HLA-B gene; Conditional P-value = 6.4 × 10−10) was detected. Although none of the non-HLA signals reached genome-wide significance (P

Background/objectives: Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely underrepresented in genomic studies. Here, we study the genetic architecture of BMI in children, young adults, and elderly individuals from the admixed population of Brazil. Subjects/methods: Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European, and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of body mass index (BMI) in three Brazilian population-based cohorts from Northeast (Salvador), Southeast (Bambui), and South (Pelotas). Results: We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p = 2.76e-06). This variant is rare in Europeans but with frequencies of similar to 3% in West Africa and has a strong female-specific effect (95% CI: 2.32-5.65 kg/m(2) per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from Sao Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains similar to 9% among women with morbid obesity from Pelotas, Sao Paulo, and Bambui. The effect size of rs114066381 is at least five times higher than the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects. Conclusions: We identified six candidate SNPs associated with BMI. rs114066381 stands out for its high effect that was replicated and its high frequency in women with morbid obesity. We demonstrate how admixed populations are a source of new relevant phenotype-associated genetic variants.

The Cardiometabolic Disorders in African-Ancestry Populations (CARDINAL) study site is a well-powered, first-of-its-kind resource for developing, refining and validating methods for research into polygenic risk scores that accounts for local ancestry, to improve risk prediction in diverse populations.

Supplemental Digital Content is available in the text., Background African populations are characterised by high genetic diversity, which provides opportunities for discovering and elucidating novel variants of clinical importance, especially those affecting therapeutic outcome. Significantly more knowledge is however needed before such populations can take full advantage of the advances in precision medicine. Coupled with the need to concisely map and better understand the pharmacological implications of genetic diversity in populations of sub-Sharan African ancestry, the aim of this study was to identify and characterize known and novel variants present within 65 important absorption, distribution, metabolism and excretion genes. Patients and methods Targeted ultra-deep next-generation sequencing was used to screen a cohort of 40 South African individuals of Bantu ancestry. Results We identified a total of 1662 variants of which 129 are novel. Moreover, out of the 1662 variants 22 represent potential loss-of-function variants. A high level of allele frequency differentiation was observed for variants identified in this study when compared with other populations. Notably, on the basis of prior studies, many appear to be pharmacologically important in the pharmacokinetics of a broad range of drugs, including antiretrovirals, chemotherapeutic drugs, antiepileptics, antidepressants, and anticoagulants. An in-depth analysis was undertaken to interrogate the pharmacogenetic implications of this genetic diversity. Conclusion Despite the new insights gained from this study, the work illustrates that a more comprehensive understanding of population-specific differences is needed to facilitate the development of pharmacogenetic-based interventions for optimal drug therapy in patients of African ancestry.

South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ~400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa., Despite linguistic and geographic diversity in South Eastern Bantu-speaking (SEB) groups of South Africa, genetic variation in these groups has not been investigated in depth. Here, the authors analyse genome-wide data from 5056 individuals, providing insights into demographic history across SEB groups.

Chloroquine/hydroxychloroquine have been proposed as potential treatments for COVID-19. These drugs have warning labels for use in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Analysis of whole genome sequence data of 458 individuals from sub-Saharan Africa showed significant G6PD variation across the continent. We identified nine variants, of which four are potentially deleterious to G6PD function, and one (rs1050828) that is known to cause G6PD deficiency. We supplemented data for the rs1050828 variant with genotype array data from over 11,000 Africans. Although this variant is common in Africans overall, large allele frequency differences exist between sub-populations. African sub-populations in the same country can show significant differences in allele frequency (e.g. 16.0% in Tsonga vs 0.8% in Xhosa, both in South Africa, p = 2.4 × 10−3). The high prevalence of variants in the G6PD gene found in this analysis suggests that it may be a significant interaction factor in clinical trials of chloroquine and hydroxychloroquine for treatment of COVID-19 in Africans.

Genomic variation in Indian populations is of great interest due to the diversity of ancestral components, social stratification, endogamy and complex admixture patterns. With an expanding population of 1.2 billion, India is also a treasure trove to catalogue innocuous as well as clinically relevant rare mutations. Recent studies have revealed four dominant ancestries in populations from mainland India: Ancestral North-Indian (ANI), Ancestral South-Indian (ASI), Ancestral Tibeto-Burman (ATB) and Ancestral Austro-Asiatic (AAA). The 1000 Genomes Project (KGP) Phase-3 data include about 500 genomes from five linguistically defined Indian-Subcontinent (IS) populations (Punjabi, Gujrati, Bengali, Telugu and Tamil) some of whom are recent migrants to USA or UK. Comparative analyses show that despite the distinct geographic origins of the KGP-IS populations, the ANI component is predominantly represented in this dataset. Previous studies demonstrated population substructure in the HapMap Gujrati population, and we found evidence for additional substructure in the Punjabi and Telugu populations. These substructured populations have characteristic/significant differences in heterozygosity and inbreeding coefficients. Moreover, we demonstrate that the substructure is better explained by factors like differences in proportion of ancestral components, and endogamy driven social structure rather than invoking a novel ancestral component to explain it. Therefore, using language and/or geography as a proxy for an ethnic unit is inadequate for many of the IS populations. This highlights the necessity for more nuanced sampling strategies or corrective statistical approaches, particularly for biomedical and population genetics research in India.

Genetic variation and susceptibility to disease are shaped by human demographic history and adaptation. We can now study the genomes of extant Africans and uncover traces of population migration, admixture, assimilation and selection by applying sophisticated computational algorithms. There are four major ethnolinguistic divisions among present day Africans: Hunter-gatherer populations in southern and central Africa; Nilo-Saharan speakers from north and northeast Africa; Afro-Asiatic speakers from north and east Africa; and Niger-Congo speakers who are the predominant ethnolinguistic group spread across most of sub-Saharan Africa. The enormous ethnolinguistic diversity in sub-Saharan African populations is largely paralleled by extensive genetic diversity and until a decade ago, little was known about detailed origins and divergence of these groups. Results from large-scale population genetic studies, and more recently whole genome sequence data, are unravelling the critical role of events like migration and admixture and environmental factors including diet, infectious diseases and climatic conditions in shaping current population diversity. It is now possible to start providing quantitative estimates of divergence times, population size and dynamic processes that have affected populations and their genetic risk for disease. Finally, the availability of ancient genomes from Africa provides historical insights of unprecedented depth. In this review, we highlight some key interpretations that have emerged from recent African genome studies.

The fifth of a series of seven H3ABioNet online lectures for Genome Wide Association Studies (GWAS) will introduce the concept of population structure/stratification (PS) and suggest why it is critical to consider PS in a GWAS. The lecture will begin by familiarizing the types of PS that are encountered and explain the factors that could cause them to appear in a GWAS dataset. It will then cover the methods that are commonly used to identify PS in a dataset and finally discuss the available computational approaches to correct for PS in a GWAS.

Background Cardiovascular diseases (CVDs) are the leading cause of non-communicable disease deaths globally, with hypertension being a major risk factor contributing to CVDs. Blood pressure is a heritable trait, with relatively few genetic studies having been performed in Africans. This study aimed to identify genetic variants associated with variance in systolic (SBP) and diastolic (DBP) blood pressure in black South Africans. Methods Genotyping was performed using the Metabochip in a subset of participants (mixed sex; median age 17.9) and their adult female caregivers (median age 41.0) from the Birth to Twenty cohort (n = 1947). Data were analysed as a merged dataset (all participants and caregivers together) in GEMMA (v0.94.1) using univariate linear mixed models, incorporating a centered relatedness matrix to account for the relatedness between individuals and with adjustments for age, sex, BMI and principal components of the genotype information. Results Association analysis identified regions of interest in the NOS1AP (DBP: rs112468105 - p = 7.18 × 10−5 and SBP: rs4657181 - p = 4.04 × 10−5), MYRF (SBP: rs11230796 - p = 2.16 × 10−7, rs400075 - p = 2.88 × 10−7) and POC1B (SBP: rs770373 - p = 7.05 × 10−5, rs770374 - p = 9.05 × 10−5) genes and some intergenic regions (DACH1|LOC440145 (DBP: rs17240498 - p = 4.91 × 10−6 and SBP: rs17240498 - p = 2.10 × 10−5) and INTS10|LPL (SBP: rs55830938 - p = 1.30 × 10−5, rs73599609 - p = 5.78 × 10−5, rs73667448 - p = 6.86 × 10−5)). Conclusions The study provided further insight into the contribution of genetic variants to blood pressure in black South Africans. Future functional and replication studies in larger samples are required to confirm the role of the identified loci in blood pressure regulation and whether or not these variants are African-specific. Electronic supplementary material The online version of this article (10.1186/s12920-018-0321-6) contains supplementary material, which is available to authorized users.

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so., Author summary Many programs have been developed to boost the technical and computational skills of scientists working in low to medium income countries (LMIC), who often struggle to remain competitive with their peers in more developed parts of the world. Typically, these programs rely on intensive workshops where students acquire and exercise these skills under the supervision of experienced trainers. However, when trainees return to their home institutions, even after extensive exposure to state of the art techniques, they often find it difficult to put the skills they have acquired into practice and to establish themselves as fully independent practitioners. We have attempted to build a framework through which teams of scientists in African research groups can demonstrate that they have acquired the necessary skills to analyze different types of genomic datasets. Three teams of scientists who have successfully submitted to this assessment exercise report their positive experiences. Many potential participants have so far declined the opportunity, and we discuss the reasons for their reluctance as well as possible ways to facilitate their engagement and provide them with incentives. We argue that assessments such as this could be part of any program aiming to develop technical skills in scientists wishing to support genomic research programs.

SLC22A2 facilitates the transport of endogenous and exogenous cationic compounds. Many pharmacologically significant compounds are transported by SLC22A2, including the antidiabetic drug metformin, anticancer agent cisplatin, and antiretroviral lamivudine. Genetic polymorphisms in SLC22A2 can modify the pharmacokinetic profiles of such important medicines and could therefore prove useful as precision medicine biomarkers. Since the frequency of SLC22A2 polymorphisms varies among different ethnic populations, we evaluated these in South African Bantu speakers, a majority group in the South African population, who exhibit unique genetic diversity, and we subsequently functionally characterized promoter polymorphisms. We identified 11 polymorphisms within the promoter and 9 single-nucleotide polymorphisms (SNPs) within the coding region of SLC22A2. While some polymorphisms appeared with minor allele frequencies similar to other African and non-African populations, some differed considerably; this was especially notable for three missense polymorphisms. In addition, we functionally characterized two promoter polymorphisms; rs138765638, a three base-pair deletion that bioinformatics analysis suggested could alter c-Ets-1/2, Elk1, and/or STAT4 binding, and rs59695691, an SNP that could abolish TFII-I binding. Significantly higher luciferase reporter gene expression was found for rs138765638 (increase of 37%; p = 0.001) and significantly lower expression for rs59695691 (decrease of 25%; p = 0.038), in comparison to the wild-type control. These observations highlight the importance of identifying and functionally characterizing genetic variation in genes of pharmacological significance. Finally, our data for SLC22A2 attest to the importance of considering genetic variation in different populations for drug safety, response, and global pharmacogenomics, through, for example, projects such as the Human Heredity and Health in Africa initiative.

The aim of this study was to identify genetic variants associated with rheumatoid arthritis (RA) risk in black South Africans. Black South African RA patients (n = 263) were compared with healthy controls (n = 374). Genotyping was performed using the Immunochip, and four-digit high-resolution human leukocyte antigen (HLA) typing was performed by DNA sequencing of exon 2. Standard quality control measures were implemented on the data. The strongest associations were in the intergenic region between the HLA-DRB1 and HLA-DQA1 loci. After conditioning on HLA-DRB1 alleles, the effect in the rest of the extended major histocompatibility (MHC) diminished. Non-HLA single nucleotide polymorphisms (SNPs) in the intergenic regions LOC389203|RBPJ, LOC100131131|IL1R1, KIAA1919|REV3L, LOC643749|TRAF3IP2, and SNPs in the intron and untranslated regions (UTR) of IRF1 and the intronic region of ICOS and KIAA1542 showed association with RA (p < 5 × 10−5). Of the SNPs previously associated with RA in Caucasians, one SNP, rs874040, locating to the intergenic region LOC389203|RBPJ was replicated in this study. None of the variants in the PTPN22 gene was significantly associated. The seropositive subgroups showed similar results to the overall cohort. The effects observed across the HLA region are most likely due to HLA-DRB1, and secondary effects in the extended MHC cannot be detected. Seven non-HLA loci are associated with RA in black South Africans. Similar to Caucasians, the intergenic region between LOC38920 and RBPJ is associated with RA in this population. The strong association of the R620W variant of the PTPN22 gene with RA in Caucasians was not replicated since this variant was monomorphic in our study, but other SNP variants of the PTPN22 gene were also not associated with RA in black South Africans, suggesting that this locus does not play a major role in RA in this population.

Access to genotyping assays enables the identification of informative markers that discriminate between cattle breeds. Identification of these markers can assist in breed assignment, improvement and conservation. The objective of this study was to identify breed informative markers to discriminate between three South African indigenous cattle breeds. Data from BovineSNP50 and GeneSeek Genomic Profiler (GGP-80K) assays were generated for Afrikaner, Drakensberger and Nguni, and were analysed for their genetic differentiation. Hereford and Angus were included as outgroups. Breeds were differentiated using principal component analysis (PCA). Single-nucleotide polymorphisms (SNPs) within the breeds were determined when minor allele frequency (MAF) was ≥ 0.05. Breed-specific SNPs were identified using Reynolds Fst and extended Lewontin and Krakauer's (FLK) statistics. These SNPs were validated using three African breeds, namely N’Dama, Kuri and Zebu from Madagascar. PCA discriminated among the breeds. A larger number of polymorphic SNPs was detected in Drakensberger (73%) than in Afrikaner (56%) and Nguni (65%). No substantial numbers of informative SNPs (Fst ≥ 0.6) were identified among indigenous breeds. Eleven SNPs were validated as discriminating the indigenous breeds from other African breeds. This is because the SNPs on BovineSNP50 and GGP-80K assays were ascertained as being common in European taurine breeds. Lower MAF and SNP informativeness observed in this study limits the application of these assays in breed assignment, and could have other implications for genome-wide studies in South African indigenous breeds. Sequencing should therefore be considered to discover new SNPs that are common among indigenous South African breeds and also SNPs that discriminate among these indigenous breeds.

Transcription regulation by the phytohormone abscisic acid (ABA) plays a key role in responses to various stresses and has been extensively studied in Arabidopsis thaliana using different expression analysis techniques. Previous studies on comparative analysis of expression regulation by ABA and ABA-related stresses demonstrated marked differences in the targets of ABA. However, as few expression experiments were available during these studies, they encompass only a subset of ABA-regulated genes. The aim of the present work was to compare gene expression regulated by ABA administration in a wider range of expression experiments. Despite diversity in the actual set of genes regulated by ABA, all ABA-regulated transcriptomes shared some basic features, such as a common induced gene set, common functional targets and involvement of common regulatory mechanisms. Moreover, the cis-regulatory architecture of genes belonging to this set is expected to be of interest because of their sensitivity to ABA and apparent independence from other experimental variables. Comparative analysis of cis-regulatory element (CRE) enrichment also identified a novel CRE that is strongly associated with ABA signalling-mediated transcription repression.

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

Background Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data. Results The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones. Conclusions Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Background HIP1 Protein Interactor (HIPPI) is a pro-apoptotic protein that induces Caspase8 mediated apoptosis in cell. We have shown earlier that HIPPI could interact with a specific 9 bp sequence motif, defined as the HIPPI binding site (HBS), present in the upstream promoter of Caspase1 gene and regulate its expression. We also have shown that HIPPI, without any known nuclear localization signal, could be transported to the nucleus by HIP1, a NLS containing nucleo-cytoplasmic shuttling protein. Thus our present work aims at the investigation of the role of HIPPI as a global transcription regulator. Results We carried out genome wide search for the presence of HBS in the upstream sequences of genes. Our result suggests that HBS was predominantly located within 2 Kb upstream from transcription start site. Transcription factors like CREBP1, TBP, OCT1, EVI1 and P53 half site were significantly enriched in the 100 bp vicinity of HBS indicating that they might co-operate with HIPPI for transcription regulation. To illustrate the role of HIPPI on transcriptome, we performed gene expression profiling by microarray. Exogenous expression of HIPPI in HeLa cells resulted in up-regulation of 580 genes (p < 0.05) while 457 genes were down-regulated. Several transcription factors including CBP, REST, C/EBP beta were altered by HIPPI in this study. HIPPI also interacted with P53 in the protein level. This interaction occurred exclusively in the nuclear compartment and was absent in cells where HIP1 was knocked down. HIPPI-P53 interaction was necessary for HIPPI mediated up-regulation of Caspase1 gene. Finally, we analyzed published microarray data obtained with post mortem brains of Huntington's disease (HD) patients to investigate the possible involvement of HIPPI in HD pathogenesis. We observed that along with the transcription factors like CREB, P300, SREBP1, Sp1 etc. which are already known to be involved in HD, HIPPI binding site was also significantly over-represented in the upstream sequences of genes altered in HD. Conclusions Taken together, the results suggest that HIPPI could act as an important transcription regulator in cell regulating a vast array of genes, particularly transcription factors and at least, in part, play a role in transcription deregulation observed in HD.

The populations of Africa harbour the greatest human genetic diversity following an evolutionary history tracing its beginnings on the continent to time before the emergence of Homo sapiens. Signatures of selection are detectable as responses to ancient environments and cultural practices, modulated by more recent events including infectious epidemics, migrations, admixture and, of course, chance. The age of high-throughput biology is not passing Africa by. African-based cohort studies and networks with an African footprint are ideal springboards for disease-related genetic and genomic studies. Initiatives like HapMap, the 1000 Genomes Project, MalariaGEN, the INDEPTH network and Human Heredity and Health in Africa are catalysts to exploring African genetic diversity and its role in the spectrum from health to disease. The challenges are abundant in dissecting biological questions in the light of linguistic, cultural, geographic and political boundaries and their respective roles in shaping health-related profiles. Will studies based on African populations lead to a new wave of discovery of genetic contributors to disease?

The presence of Early and Middle Stone Age human remains and associated archeological artifacts from various sites scattered across southern Africa, suggests this geographic region to be one of the first abodes of anatomically modern humans. Although the presence of hunter-gatherer cultures in this region dates back to deep times, the peopling of southern Africa has largely been reshaped by three major sets of migrations over the last 2000 years. These migrations have led to a confluence of four distinct ancestries (San hunter-gatherer, East-African pastoralist, Bantu-speaker farmer and Eurasian) in populations from this region. In this review, we have summarized the recent insights into the refinement of timelines and routes of the migration of Bantu-speaking populations to southern Africa and their admixture with resident southern African Khoe-San populations. We highlight two recent studies providing evidence for the emergence of fine-scale population structure within some South-Eastern Bantu-speaker groups. We also accentuate whole genome sequencing studies (current and ancient) that have both enhanced our understanding of the peopling of southern Africa and demonstrated a huge potential for novel variant discovery in populations from this region. Finally, we identify some of the major gaps and inconsistencies in our understanding and emphasize the importance of more systematic studies of southern African populations from diverse ethnolinguistic groups and geographic locations.